THE ROLE OF PHYSICAL HEALTH ON LIFE SATISFACTION IN PEOPLE WITH

SERIOUS MENTAL ILLNESS

A THESIS IN

Psychology

Presented to the Faculty of the University

of Missouri-Kansas City in partial fulfillment of

the requirements for the degree

MASTER OF ARTS

by

Amy Lee Barnes

B.A., University of Illinois at Springfield, 2007

Kansas City, Missouri

2011

© 2011

AMY LEE BARNES

ALL RIGHTS RESERVED

ii

THE ROLE OF PHYSICAL HEALTH ON LIFE SATISFACTION

IN PEOPLE WITH SERIOUS MENTAL ILLNESS

Amy Lee Barnes, Candidate for the Master of Arts Degree

University of Missouri-Kansas City, 2011

ABSTRACT

The purpose of this study was to investigate the contribution of physical health and

mental health on quality of life reports in people with serious mental illness. Examining the

role of physical health is especially important in this population due to increased rates of

medical comorbidity. This study differs from previous research as it directly compares the

influence of mental health factors to physical health factors in a quality of life model. A

total of 49 participants completed a quality of life inventory, a health survey, and provided

subjective ratings of current clinical symptoms. Results indicate that people with SMI are

at least as concerned with their physical health as they are their mental health. Findings

further suggest that physical health is a stronger predictor of overall quality of life, even

after controlling for depressive and psychiatric symptoms, and limitations due to mental

health. Areas of future research are discussed.

iii

APPROVAL PAGE

The faculty listed below, appointed by the Dean of the College of Arts and Science

have examined a thesis titled “The Role of Physical Health on Life Satisfaction in People

with Serious Mental Illness,” presented by Amy L. Barnes, candidate for the Master of

Arts degree, and certify that in their opinion it is worthy of acceptance.

Supervisory Committee

Melisa V. Rempfer, Ph.D., Committee Chair

Department of Psychology

Jennifer D. Lundgren, Ph.D.

Department of Psychology

Jared Bruce, Ph.D.

Department of Psychology

iv

CONTENTS

ABSTRACT ................................................................................................................ ii

LIST OF ILLUSTRATIONS ......................................................................................... vii

LIST OF TABLES ....................................................................................................... viii

Chapter

1. OVERVIEW ....................................................................................................... 1

2. REVIEW OF LITERATURE............................................................................... 3

Quality of Life as Outcome Assessment ............................................................... 3

Quality of Life Reported by People with Serious Mental Illness .......................... 4

Correlates with Quality of Life ............................................................................ 6

Medical Comorbidity ........................................................................................... 8

Comprehensive View of Health ......................................................................... 10

Health Related Quality of Life ........................................................................... 11

The Current Study ............................................................................................. 12

3. METHODOLOGY ............................................................................................ 14

Participants ........................................................................................................ 14

Procedure .......................................................................................................... 14

Measures ........................................................................................................... 15

Quality of Life Enjoyment and Satisfaction Questionnaire ..................... 15

Short Form Health Survey ...................................................................... 16

Hamilton Depression Rating Scale ......................................................... 17

Brief Psychiatric Rating Scale-Expanded ............................................... 17

v

Statistical Analyses ............................................................................................ 18

Hypothesis One ...................................................................................... 18

Hypothesis Two ..................................................................................... 18

4. RESULTS ......................................................................................................... 19

Descriptive Data ................................................................................................ 19

Data Analysis .................................................................................................... 22

Hypothesis One ...................................................................................... 22

Hypothesis Two ..................................................................................... 23

Secondary Model ................................................................................... 27

5. DISCUSSION ................................................................................................... 30

Limitations ........................................................................................................ 33

Conclusion ........................................................................................................ 34

REFERENCES ............................................................................................................. 36

VITA .......................................................................................................................... 42

vi

ILLUSTRATIONS

Figure Page

1. Role limitations due to physical and mental health among individuals with

serious mental illness 22

vii

TABLES

Table Page

1. Demographic Characteristics 20

2. Means and Standard Deviations for All Measures 21

3. Summary of Bivariate Correlations Among Quality of Life and the HAM-D,

BPRS-E, MHC, and PHC 25

4. Summary of R2 Changes at Each Step in the Hierarchical Regression 26

5. Summary of R2 and F Values at Each Step in the Hierarchical Regression Not

Controlling for Depressive Symptoms 28

1

CHAPTER 1

OVERVIEW

The purpose of this study was to investigate predictors of quality of life in people

with serious mental illness (SMI). Quality of life measurement in people with SMI is an

evolving concept that consists of multiple domains including cognition, social and

occupational functioning, psychiatric symptoms, and health. While people with SMI

experience higher rates of medical comorbidity than the general population, quality of life

research to date has focused primarily on the mental health of people with SMI (Narvaez,

Twamley, McKibbin, Heaton, & Patterson, 2008), and neglected the domain of physical

health. Approximately 70% of people with schizophrenia have at least one medical health

condition and up to 33% have three or more concurrent health conditions. As such, the

early mortality rate among people with SMI is estimated at five times higher than the

general population (Kelly, Boggs, & Conley, 2007). Because of the high rate of medical

co-morbidities in this population, it is important to examine the effects of physical health,

in addition to mental health, on quality of life reports. This study investigated how

limitations due to physical health and mental health predict quality of life reports in people

with SMI. Including physical and mental health components into a unified view of overall

quality of life may better inform the currently fragmented system of medical and mental

healthcare for people with SMI (Miller, Pashall III, & Svendsen, 2006). Results found that

people with SMI reported lower quality of life than the general population, however did

not report significant differences between limitations due to physical health versus mental

2

health. Physical health did emerge as the strongest predictor of quality of life, above other

factors such as depressive and psychiatric symptoms and role limitations due to mental

health. Overall the results of this study provide evidence of the effect of physical health on

quality of life and the importance of including physical health into comprehensive

treatment and intervention services for people with serious mental illness.

3

CHAPTER 2

REVIEW OF THE LITERATURE

Quality of Life as Outcome Assessment

Quality of life in the serious mental illness literature is a broad concept

encapsulating many different domains including severity of psychiatric symptoms,

cognition, occupational and social functioning, physical health and the co-occurrence of

other psychiatric illnesses such as depression (Hewitt, 2007). Quality of life ratings by

people with SMI have been associated with differing levels of cognitive functioning, both

positive and negative psychiatric symptoms, access to social services, interpersonal

relationships, functional ability (occupational and daily living skills), and demographic

factors such as age, gender, education, and living situation (Matsui, Sumiyoshi, Arai,

Higuchi, & Kurachi, 2008; Narvaez et al., 2008).

Although current research in this area has failed to provide a uniform definition of

quality of life for people with mental illness, there are two general categories that have

been examined: 1) the subjective reports of people with SMI regarding the perception of

their own wellbeing, ability to function in daily life, and resources available to them and 2)

both subjective and objective reports of role limitations due to their mental health, physical

health and social and occupational functioning (Bow-Thomas, Velligan, Miller, & Olsen,

1999; Eack & Newhill, 2007). Subjective quality of life typically focuses on self-reports of

life satisfaction with family and social relationships, overall life satisfaction, and

functioning in activities of daily living. Subjective measures of quality of life also include

self-reports of severity of positive, negative and depressive symptoms. Objective quality of

4

life indicators are typically observable factors such as employment, living situation, marital

status, and level of involvement in social activities (Narvaez et al., 2008). Current research

has found the integration of both objective and subjective quality of life indicators to be

more meaningful than examining either of them separately (Auquier et al., 2003).

Quality of life in people with SMI has become an important outcome assessment

for both research and treatment (Dickerson et al., 2008; Evans, Banerjee, Leese, & Huxley,

2007; Folsom et al., 2009; Narvaez et al., 2008). Whereas cognition and psychiatric

symptoms (both positive and negative) have typically been viewed as important objective

indicators of quality of life, the measurement of subjective quality of life may be more

meaningful in terms of improving overall quality of life in this population (Folsom et al.,

2009). Indeed, there has been a shift in the mental health system toward a more personal

recovery model that recognizes the importance of subjective experience (e.g., Andresen,

Caputi, & Oades, 2010). As quality of life becomes an important outcome goal in mental

health care and research, it is important to identify the primary domains that influence

subjective quality of life reports, especially in the SMI population (Evans et al., 2007;

Ritsner, Gibel, & Ratner, 2006).

Quality of Life Reported by People with Serious Mental Illness

Compared with the general population, people with mental illness report a lower

overall quality of life. Evans et al. (2007) compared quality of life ratings between people

with serious mental illness, people with common mental disorders (CMD) and people

without a mental health diagnosis in a two year longitudinal study. Participants with SMI

were included based on the presence of delusions, hallucinations, thought disorder, a

5

psychotic illness of at least two years, and a minimum of two inpatient admissions related

to their mental health. Participants were categorized into the CMD group if they reported

moderate mental health symptoms. The control group reported no mental health symptoms

and was considered asymptomatic. Quality of life was assessed using the Lancashire

Quality of Life Profile (LQOLP) for the SMI group and the Quality of Life in the

Community Scale (QOL-COMM) for the CMD and controls. These instruments included

both subjective and objective assessment in life domains such as work, leisure, finance,

living situation, family, social life and health. Health was a broad domain encompassing

both mental and physical health combined. Significant differences were observed between

the control group and both the SMI and CMD groups. Further, in the majority of life

domains, the SMI and CMD groups did not significantly differ from each other. The

results of this research show that people with mental illness and those with common

mental disorders report lower quality of life ratings than the general population (Evans et

al., 2007).

Ritsner, Kurs, Kostizky, Ponizovsky, & Modai (2002) reported further evidence of

lower quality of life ratings using the Quality of Life Enjoyment and Satisfaction

Questionnaire (Q-LES-Q) and the Lancashire Quality of Life Profile (LQOLP) in people

with schizophrenia compared with people without mental illness. In this study, 199

participants with schizophrenia were administered a neuropsychological test battery and

were interviewed about current symptom severity and type (positive and negative). Results

indicate that for overall quality of life, individuals with schizophrenia reported

significantly lower subjective quality of life scores compared with control participants.

6

Further analysis revealed that both measures were able to discriminate between persons

with and without mental illness in the specific domains of physical health, leisure activities

and social relationships. The Q-LES-Q was able to discriminate among groups in all

domains including health, work, leisure, social relationships, life satisfaction, perceived

quality of life index, subjective feelings, household duties and general activities. People

with SMI typically report their quality of life as significantly lower than the general

population (Ristner et al., 2002). As quality of life becomes an important target of outcome

research, identifying key differences in quality of life in the SMI population can help to

guide and focus current quality of life research.

Schechter, Endicott, & Nee (2007) also found that people with a history of mental

illness report lower quality of life ratings than people with no history of mental illness and

people with only one episode of mental illness. The results of this study found that people

who were currently mentally ill reported the lowest quality of life, followed by people with

a history of mental illness, who were not currently mentally ill. Quality of life was highest

in people with either no history or only one episode of mental illness. These findings

demonstrate not only that people with mental illness report lower quality of life than the

general population, but also that a history of mental illness, even in the absence of current

symptoms, is negatively associated with quality of life ratings.

Correlates with Quality of Life

To date, much of the research on quality of life in serious mental illness has

focused on its relationship with cognitive and clinical symptoms. With regard to cognitive

functioning, existing research generally indicates that quality of life may be only modestly

7

related to cognitive functioning, however results are mixed. In current models, cognition

failed to continue to be a significant predictor with quality of life after adding other factors

such as clinical symptoms and medical comorbidity. Matsui et al. (2008) investigated the

effect of executive functioning and clinical symptoms on quality of life ratings in people

with schizophrenia. A total of 53 participants were given a battery of neuropsychological

tests. Clinical symptoms and quality of life were measured through interview by an

experienced clinician. Results showed that memory and social skill performance predicted

quality of life scores. Additionally, negative clinical symptoms (avolition and anhedonia)

were strongly negatively associated with quality of life scores. Interestingly, after

controlling for clinical symptoms, cognition was no longer strongly associated with the

participant’s quality of life ratings. Matsui et al. (2008) reported a small effect size when

examining the relationship between various neuropsychological measures and quality of

life impairment in people with schizophrenia.

These results are consistent with previous research by Wegener et al. (2005) who

also found moderate correlations between cognition and quality of life. Overall, however,

cognitive ability was less predictive of quality of life than were negative symptoms.

Negative symptoms, such as anhedonia or avolition, in people with SMI were more

strongly associated with quality of life than were positive symptoms. While previous

research has found a significant relationship between negative symptoms, severity of

symptoms and quality of life, the effect sizes were generally small and occasionally non-

significant when controlling for depressive symptoms (Eack & Newhill, 2007; Holloway

& Carson, 1999; Narvaez et al., 2008; Salokangas, Honkonen, Stengard, & Koivisto,

8

2006), which can be difficult to differentiate from primary negative symptoms in people

with SMI.

Overall, research is inconsistent in its findings between symptomology and

subjective quality of life. Ritsner et al. (2006) found that improvements in quality of life

were positively correlated with reductions in clinical and depressive symptoms, however

Narvaez (2008) found that symptom reduction alone did not translate into better subjective

quality of life. In a meta-analytic review by Tolman and Kurtz (2010), effect sizes between

cognition, executive functioning and quality of life were generally small, suggesting that

there may be additional individual determinants of quality of life that may be more

meaningful. Ritsner et al. (2006) suggested that medical comorbidity may be an underlying

factor influencing both executive functioning deficiencies (including cognition) and lower

quality of life ratings. Ritsner recommended future research using integrated global and

health related quality of life measures such as the Q-LES-Q, which uses a broader domain

of health including both physical and mental health satisfaction.

Medical Comorbidity

Medical comorbidity is much higher in the SMI population than in the general

population and has become a focus of great concern (Kelly et al., 2007). Mortality rates in

the SMI population are much higher than among people without SMI. The current average

life expectancy of the general population is approximately 76 years; however, the life

expectancy of people with schizophrenia is only 61 years (Kelly et al., 2007). As a result,

serious mental illness is considered a life shortening illness. As much as 70% of people

with schizophrenia have increased rates of medical comorbidities and as much as 33% of

9

this population suffers from at least three or more common medical disorders including

hypertension, chronic obstructive pulmonary disease, and diabetes which are all associated

with increased mortality rates and cardiovascular disease (Kelly et al., 2007).

Coronary heart disease (CHD) is currently the leading cause of death of all people

in the United States and people with SMI are at elevated risk (Kelly, et al., 2007). In the

general population, men have a 7.0% risk of developing CHD and women have a 4.2%

risk. However, people with serious mental illness show even greater risks with men having

a 9.4% risk and women having a 6.3% risk of developing CHD. Risk factors that influence

the development of coronary heart disease in the psychiatric population include lifestyle

factors, medication side effects and genetic predispositions (Kelly et al., 2007). These

factors are particularly challenging to address in the SMI population due to difficulties

with executive functioning, avolition, comorbid substance use, motivation, and lack of

integrated treatment of mental and medical health care.

Greater physical health symptoms are typically associated with greater mental

health symptoms. People with SMI have greater somatic concerns than the general

population and seek emergency hospital care significantly more frequently than people

without SMI (Hackman et al., 2006). Dixon, Postrado, Delhanty, Fischer, & Lehman,

(1999) found that the number of increased medical conditions was related to lower

subjective ratings of physical health, mental health and increased depressive symptoms.

Dixon et al. (1999) found that, consistent with the general population, people with SMI

also reported lower subjective quality of life ratings of both physical and mental health in

the presence of increased medical illness. Dixon et al. also showed that people with an

10

increased number of medical illnesses were able to accurately rate their physical health as

poor. This level of accurate insight into physical health is noteworthy, in light of research

on the limits of insight into mental illness for this population (Karow et al., 2008). As

pointed out by Dixon et al. (1999), the inability to appropriately identify and describe a

mental health problem is distinct from inability to appropriately identify and describe a

medical health problem. Increased medical comorbidity, increased mortality and lower

subjective quality of life ratings provide evidence of the impact of poor physical health on

quality of life in people with serious mental illness.

Comprehensive View of Health

Co-occurring physical health problems, prevalent in the serious mental

illness population may represent a distinct area of concern when evaluating the general

domain of health, which typically encompasses both mental and physical health. Dickerson

et al. (2008) found that people with SMI and co-morbid Type II diabetes reported

significantly lower health related quality of life than people with SMI who did not have

diabetes. Interestingly, among those with diabetes, there were no differences in the mental

health domains of quality of life between people with and without a serious mental illness

diagnosis. These results are also consistent with research by Salokangas et al. (2006) that

showed people with schizophrenia and with severe physical illnesses reported significantly

lower subjective quality of life both at baseline and at a three year follow up than people

with schizophrenia without physical illness.

For this reason, recent quality of life research has focused on health related quality

of life measures, which integrate both physical and mental health domains. The 2008 study

11

by Dickerson et al. purported to be the first in examining the impact of diabetes on

subjective quality of life ratings in people with SMI. Due to the positive relationship found

between physical health and quality of life and mental health and quality of life, it is

important to view health as encompassing both physical and mental characteristics. This

indicates an encouraging direction in SMI research incorporating physical health in

addition to mental health concerns specifically when looking at quality of life.

Health Related Quality of Life

Health related quality of life (HRQoL) measurement typically encompasses both

subjective perceptions and observable (objective) characteristics of health. Because people

with serious mental illness typically struggle with physical health issues in addition to

mental health issues, it may be more meaningful in this population to focus on health

related quality of life, which adopts an integrated view of health including both physical

and mental health limitations, rather than traditional quality of life measures. Originally

designed to measure the impact of chronic disease on quality of life in people with cancer,

HRQoL assessments have expanded into psychological research as an approach to

wellness that includes mental and physical health (Porzsolt et al., 1996). HRQoL is defined

as subjective reports of physical, emotional, cognitive and social and occupational

functioning, and is intended to capture a wider array of concerns than traditional global

quality of life assessments. This type of measurement is able to assess the impact of a

broad definition of health and its impact on subjective life satisfaction (Auquier et al.,

2003; Folsom et al., 2009; Porzsolt et al., 1996).

12

Health related quality of life is distinct from global quality of life by addressing

physical and mental health separately, whereas the most recent definitions of global quality

of life represent overall life satisfaction, including three main dimensions of

satisfaction/wellbeing: biological, psychological and social functioning (Marwaha et al.,

2008). Quality of life is a developing concept. However, understanding the determinants

of subjective satisfaction in the serious mental illness population is important in order to

target areas for intervention. Specific to the SMI population, these include physical health,

psychiatric symptoms, cognition and activities of daily living (ADL) in addition to

demographic factors such as age, gender, education and socio-economic status. Currently,

the majority of quality of life research in the serious mental illness population has focused

primarily on mental health and social/occupational functioning. Recent quality of life

research is expanding to simultaneously examine clinical, cognitive and functional

predictors of quality of life, and health in the SMI population (Folsom et al. 2009; Narvaez

et al., 2008). Future research can utilize health related quality of life measures as outcome

assessments, thereby encompassing the physical and mental health care concerns of people

with serious mental illness.

The Current Study

The purpose of this study was to examine the effects of physical health and mental

health separately on subjective reports of overall quality of life in people with serious

mental illness. As discussed previously, the impact of physical health, in addition to mental

health, should be considered in psychological QOL research. Adopting an integrated view

of health using the construct of health related quality of life can facilitate the identification

13

of individual predictors of life satisfaction, especially in the serious mental illness

population. Specifically it is predicted that among persons with SMI, satisfaction with

physical health will be lower than subjective reports of satisfaction with mental health. As

a result of increased physical illness in the SMI population, it is predicted that the physical

health component (PHC) of quality of life will be a stronger predictor of overall life

satisfaction than will the mental health component (MHC) even after controlling for the

effects of depression.

The first aim of this study was to determine if people with serious mental illness

more subjectively rate satisfaction with physical health as lower than satisfaction with

mental health. The first hypothesis was that people with serious mental illness would

report overall lower subjective satisfaction with their physical health than their mental

health.

A second aim of this study was to determine if role limitations due to physical

health concerns influenced quality of life ratings greater than role limitations due to mental

health concerns. It was hypothesized that the concurrent subjective satisfaction of physical

health of people with serious mental illness would be more predictive of overall life

satisfaction than would mental health.

14

CHAPTER 3

METHODOLOGY

Participants

A total of 49 participants (24 female and 25 male) with serious mental illness, ages

18 to 65 (mean = 45.51 ±10.57), were recruited from a community mental health center

day program. Participants were included in the study if they had been previously diagnosed

with schizophrenia, schizoaffective disorder, bipolar disorder I or II, or major depressive

disorder (MDD). The Structured Clinical Interview for DSM Disorders (SCID; First,

Spitzer, Gibbon, & Williams, 1996) was used to confirm diagnosis. Exclusionary criteria

included known neurological disease, developmental disability, significant

sensory/physical impairment that would affect task performance (e.g. blindness), or

substance abuse/dependence in the prior 30 days. All study procedures received approval

from the institutional review board at the University of Missouri-Kansas City. This

research was conducted as part of larger study investigating cognition and everyday life

skills.

Procedure

Participants were recruited via case management staff at a community mental

health center. A brief phone screening was administered by researchers in order to

determine study eligibility. Testing was completed in a private room at the community

mental health center in one or two sessions totaling 3 to 5 hours. All participants provided

informed consent. In addition to a demographic profile which included a checklist of

15

current medical conditions, participants also completed a quality of life inventory, and a

health survey. Participants also completed a measure of depression and were interviewed

about current psychiatric symptoms, as described below.

Measures

Quality of Life, Enjoyment, and Satisfaction Questionnaire

An abbreviated form of the Q-LES-Q, the Quality of Life Enjoyment and

Satisfaction Questionnaire (Q-LES-Q-18; Endicott, Nee, Harrison, & Blumenthal, 1993;

Ritsner, Kurs, Gibel, Ratner, & Endicott, 2005) was used to measure overall quality of life.

The Q-LES-Q-18 produces a general or overall quality of life index score, which was used

as the outcome variable for the purposes of this study. A total of 18 core questions address

physical health (items 1-4), subjective feelings (items 5-9), leisure time activities (items

10-12), social relationships (items 13-17) and satisfaction with medication (item 18). The

Q-LES-Q-18 also includes five additional questions that ask about overall satisfaction with

social relationships, the ability to function in daily life, economic status, overall sense of

wellbeing, and overall life satisfaction and contentment during the past week. The general

quality of life index score is derived by taking the average of scores for the first 18 items.

Ritsner et al. (2005) evaluated 339 participants with SMI and found the Q-LES-Q-

18 to be a highly reliable, valid and stable measure of self-reported life satisfaction.

Cronbach’s alpha was between .74 and .97 indicating a moderate to high internal

consistency. Construct validity was demonstrated through the ability of the Q-LES-Q-18 to

discriminate between participants with and without SMI, with control participants yielding

16

higher mean scores (reporting higher quality of life). Test-retest reliability scores were

high, 0.90 for outpatient participants and 0.86 for control participants.

Short Form Health Survey

The Short Form Health Survey (SF-36; Ware, Snow, Kosinski, & Gandek, 1993) is

a 36 item generic measure of subjective health which includes questions about function

and dysfunction, distress, well-being, and both objective and subjective evaluations of

general health status (Hewitt, 2007). Widely used in many populations as a health related

quality of life assessment, the SF-36 contains two primary components, the physical health

component (PHC) and the mental health component (MHC), which were used as predictor

variables in predicting quality of life (Hewitt, 2007; Ware et al., 1993).

The SF-36 has extensive reliability and validity evidence, including research in the

serious mental illness population (Auquier et al., 2003; Burke, Burke, Baker, & Hillis,

1995; Hewitt, 2007; Pukrop et al., 2003). Internal consistency estimates for the general

population exceed 0.90 for both the PHC and MHC summary scales (Ware et al., 1994).

Median internal consistencies for the SF-36 dimensions are 0.79 (range 0.60 to 0.92) for

people with depression and 0.83 (range 0.71 to 0.89) for people with schizophrenia.

Discriminant validity is evidenced through correlational research showing a non-

significant relationship between psychiatric symptoms and quality of life ratings in people

with schizophrenia (Pukrop et al., 2003). Convergent validity is evidenced by strong

positive correlations between the SF-36 and the S-QoL (Schizophrenia Quality of Life;

Auquier et al., 2003), and MSQoL (Modular System for Quality of Life; Pukrop et al.,

2003). Intra-class correlations for test-retest reliability of the SF-36 (paper version) range

17

from 0.54 to 0.88 among people with psychiatric symptoms (Burke et al., 1995). For this

study, the SF-36 scales of interest were the MHC and PHC, which were calculated into

standardized scores using means and standard deviations from the 1998 U.S. general

population norms. Standardized scores were created using the SF-36v2 software scoring

program. These scales share a common metric, with a range of 0-100, a mean of 50, and a

standard deviation of 10.

Hamilton Depression Rating Scale

The Hamilton Rating Scale for Depression (HAM-D; Hamilton, 1967) is a widely

used instrument designed to quantitatively assess the severity of depressive symptoms.

Consisting of 23 items, the HAM-D assesses multiple symptoms of depression including

suicidality, anhedonia, insomnia, anxiety, and feelings of helplessness and guilt. Higher

scores indicate more depressive symptomology. The HAM-D was chosen as a predictor for

this study because it is reportedly less sensitive to somatic complaints, common in the

serious mental illness population, than other measures of depression (Hamilton, 1967).

Brief Psychiatric Rating Scale- Expanded

The Brief Psychiatric Rating Scale-Expanded (BPRS–E; Lukoff, Nuechterlein, &

Ventura, 1986) is a rapid assessment of psychopathology symptoms. The BPRS-E is

administered via clinical interview and responses are scored on a 7 point Likert type scale

ranging from “not present” to “extremely severe”. Ratings of tension, emotional

withdrawal, mannerisms/posturing, motor retardation, blunted affect and

uncooperativeness are scored by the interviewer based on clinical observation. Ratings of

18

conceptual disorganization, unusual thought content, anxiety, guilt, grandiosity, depressed

mood, hostility, somatic concern, hallucinations, and suspiciousness are provided through

self-report. Answers are scored from 1 to 7 for each item and a summative score indicates

current levels of psychopathology symptoms within the last two weeks. For the purposes

of this study, only the summative score was used as a predictor to assess current

psychiatric symptoms.

Statistical Analysis

Hypothesis One

The first hypothesis was that people with SMI would report lower satisfaction with

their physical health than their mental health. In addition to a total overall score, the SF-36

yields two sub-domain scores: a mental health component (MHC) and a physical health

component (PHC). A paired samples t-test was used to determine if there were significant

mean differences between reported satisfaction with physical health and mental health

scores on the SF-36.

Hypothesis Two

The second hypothesis predicted that physical health would influence overall

quality of life greater than mental health. In order to identify significant predictors of

quality of life in people with serious mental illness, hierarchical linear regression was used

with overall quality of life (Q-LES-Q) as the outcome variable and depression (HAM-D;

step one of regression), psychiatric symptoms (BPRS-E; step two), and role limitations due

to mental (MHC; step three) and physical health (PHC; step four) as predictor variables.

19

CHAPTER 4

RESULTS

Descriptive Data

Of this sample, 46.9% (n=23) had a SCID-confirmed diagnosis of schizophrenia,

10.2% (n=5) with schizoaffective disorder, 28.6% (n=14) with major depressive disorder,

and 12.2% (n=6) with bipolar disorder. One participant did not fully complete the SCID,

but had a chart diagnosis of schizophrenia. Participants were primarily African American

(63.3%, n=31), followed by Caucasian (26.5%, n=13), and multi-racial (10.2%, n=5). The

majority of participants reported never being married (46.9%, n=23), and remaining

participants reported being either divorced/ widowed/separated (36.7%, n=18) or

married/living together (16.3%, n=8). Reported educational levels included some high

school (34.7%, n=17), high school graduate or GED (28.6%, n=14), post high school

(2.0%, n=1), some college (32.7%, n=16) and college beyond a bachelor’s degree (2.0%,

n=1). Most participants reported living independently (65.3%, n=32) while remaining

participants reported living with relatives (14.3%, n=7), living in supervised care housing

(12.2%, n=6), being homeless (6.1%, n=3), or living in a long term care facility (2.0%,

n=1). Approximately 91.8% (n=45) reported not being currently employed. See Table 1.

20

Table 1. Descriptive Characteristics

Total N = 49 N (%)

Gender

Male 25 (51%)

Female 24 (49%)

Race

African American 31 (63.3%)

Caucasian 13 (26.5%)

Multi-Racial 5 (10.2%)

Marital Status

Never married 23 (46.9%)

Divorced/Widowed/Separated 18 (36.7%)

Married/Living together 8 (16.3%)

Education

Less than high school 17 (34.7%)

High school/GED 14 (28.6%)

Post high school/no college 1 (2%)

Some college 16 (32.7%)

College beyond 4 year degree 1 (2%)

Living Situation

Lives independently 32 (65.3%)

Lives with relatives 7 (14.3%)

Supervised care housing 6 (12.2%)

Long term care facility 1 (2%)

Homeless 3 (6.1%)

Vocational Status

Unemployed 45 (91.8%)

Employed 4 (8.2%)

21

There were no significant group differences on predictor or outcome variables

based on diagnosis, age, race, marital status, or living status, however males reported

significantly lower HRQOL due to physical health than females. Means and standard

deviations for all primary measures are reported in Table 2.

Table 2. Means and Standard Deviations for All Measures

Total N = 49 Mean (SD)

Q-LES-Q 3.43 (0.60)

HAM-D 19.51 (10.50)

BPRS-E 44.92 (9.84)

MHC (n = 47) 39.38 (11.90)

PHC (n = 47) 42.76 (9.75)

NOTE: Q-LES-Q = Quality of Life Enjoyment and Satisfaction Questionnaire-23 (Score is

average of questions 1-18), HAM-D = Hamilton Depression Rating Scale, BPRS-E = Brief

Psychiatric Rating Scale-Expanded, MHC = Mental Health Component of the SF-36,

PHC = Physical Health Component of the SF-36.

22

Data Analysis

Hypothesis One

A paired samples t-test was used to determine if participant’s standardized scores

on the PHC (M=42.76, SD=9.75) significantly differed from scores on the MHC

(M=39.38, SD=11.90) of the SF-36 health related quality of life measure. Our first

prediction was not confirmed and results showed that on average, PHC scores did not

significantly differ from MHC scores within the SMI sample, t(46)=1.40, p=.169, d=.29.

These results provide evidence that on average, participants did not report greater role

limitations due to physical health than mental health. See figure 1.

Figure 1.

23

Hypothesis Two

Hierarchical regression was used in order to identify significant predictors of

quality of life in people with SMI. Quality of life (Q-LES-Q) was used as the outcome

variable and depression (HAM-D), psychiatric symptoms (BPRS-E), and role limitations

due to physical (PHC) and mental health (MHC) were predictor variables. Predictors were

entered in individual blocks with the HAM-D being entered in Step 1, the BPRS-E in Step

2, MHC in Step 3, and PHC in Step 4. The rationale for this order of entry included

controlling for the effects of depression and psychiatric symptoms on overall quality of

life. It was predicted that role limitations due to physical health would significantly predict

quality of life above what could be explained by depressive and psychiatric symptoms and

mental health factors, therefore MHC was entered prior to PHC. Results are summarized in

Tables 3 and 4.

Bivariate correlations revealed significant relationships among quality of life and

the following measures: the HAM-D (r = -.383, p<.05), the number of reported medical

conditions (r = -.481, p<.001), the MHC (r = .460, p<.001), and the PHC (r = .524,

p<.001). Demographic factors such as educational level, psychiatric symptoms as

measured by the BPRS-E, age, gender, race, marital status, living situation and work status

were not significantly related to quality of life scores in this sample. All correlations were

in the expected direction.

The overall regression, including all four predictors, was statistically significant, R

= .78, R2 = .61, adjusted R

2 = .57, F(4, 42) = 16.14, p<.001, indicating that overall quality

24

of life scores were predicted quite well from this set of four variables, with approximately

78% of the variance in quality of life scores accounted for by the model.

To assess the contributions of individual predictors, the t ratios for the individual

regression slopes were examined for each variable in the step when it first entered the

analysis. In Step 1, depression was statistically significant, t(45) = -2.33, p<.05, R2 = .107.

Psychiatric symptoms as measured by the BPRS-E did not significantly increase R2 when it

was entered in Step 2, t(44) = -.193, p>.05, R2∆ < .001, F∆=.037. MHC scores significantly

increased R2 when it was entered in Step 3, [t(43) = 2.45, p<05, R

2∆ = .109, F∆=5.99]

indicating that less role limitations due to mental health significantly predicted higher

overall quality of life scores. PHC significantly increased R2

when it was entered into the

fourth and final step, [t(42) = 6.43, p<.001, R2∆ = .388, F∆=41.38] indicating that physical

health significantly predicted overall quality of life scores above what could be explained

by depressive and psychiatric symptoms and role limitations due to mental health. The

slopes of all predictors had the expected signs. Results are summarized in Table 4.

25

Table 3. Summary of Bivariate Correlations Among Quality of Life and the HAM-D,

BPRS-E, MHC and PHC.

Quality of Life HAM-D BPRS-E MHC

HAM-D -.383**

BPRS-E -.255 .685***

MHC .460** -.656*** -.387***

PHC .524*** -.088 -.085 -.167

NOTE: HAM-D = Hamilton Depression Rating Scale, BPRS-E = Brief Psychiatric Rating

Scale-Expanded, MHC = Mental Health Component of the SF-36, PHC = Physical Health

Component of the SF-36. *p is significant at the 0.05 level (two-tailed), **p is significant

at the 0.01 level (two-tailed), ***p is significant at the 0.001 level (two-tailed).

26

Table 4. Summary of R2 Changes at Each Step in the Hierarchical Regression.

B (SE) R

2∆ F∆

Step 1

Constant 3.765 (175)

HAM-D -.018 (.008) -.328* .107*

Step 2

Constant 3.384 (.401)

HAM-D -.017 (.011) -.302

BPRS-E -.002 (.011) -.038 .001 .037

Step 3

Constant 2.774 (.576)

HAM-D .001 (.013) .026

BPRS-E -.005 (.011) -.094

MHC .021 (.009) .441* .109* 5.99*

Step 4

Constant .374 (.557)

HAM-D .014 (.009) .255

BPRS-E -.006 (.008) -.096

MHC .034 (.007) .700**

PHC .039 (.006) .656** .388*** 41.38***

NOTE: One predictor entered in each step of the model in a user-determined sequence.

HAM-D = Hamilton Depression Rating Scale, BPRS-E = Brief Psychiatric Rating Scale-

Expanded, MHC = Mental Health Component of the SF-36, PHC = Physical Health

Component of the SF-36. *p is significant at the 0.05 level (two-tailed), **p is significant

at the 0.01 level (two-tailed), ***p is significant at the 0.001 level (two-tailed).

27

Secondary Model

A separate hierarchical regression was used to identify significant predictors of

quality of life in people with serious mental illness, without controlling for depression.

Predictors were entered in individual blocks with the BPRS-E being entered in Step 1,

MHC in Step 2, and PHC in Step 3. The overall regression, including all three predictors,

was statistically significant, [R = .76, R2 = .58, adjusted R

2 = .55, F(3, 43) = 20.15, p<.001],

indicating that overall quality of life scores could be predicted quite well from this set of

three variables, with approximately 76% of the variance in quality of life scores accounted

for by the model. Psychiatric symptoms again were not able to significantly predict overall

quality of life [t(45) = .27, p>.05, R2 = .061], however both MHC [t(42) = 5.27, p<.001,

R2∆ = .157, F∆=8.80] and PHC [t(42) = 6.16, p<.001, R

2∆ = .367, F∆=37.99] remained

significant, even without controlling for depressive symptoms. Model summary is reported

in table 5.

28

Table 5. Summary of R2 and F Values for the Model at Each Step in the Hierarchical

Regression Not Controlling for Depressive Symptoms

Predictors Included R

2 for Model F for Model F∆

BPRS-E .061 2.90

MHC .217 6.10** 8.80*

PHC .584 20.15*** 37.99***

NOTE: BPRS-E = Brief Psychiatric Rating Scale-Expanded, MHC = Mental Health

Component of the SF-36, PHC = Physical Health Component of the SF-36. *p is

significant at the 0.05 level (two-tailed), **p is significant at the 0.01 level (two-tailed),

***p is significant at the 0.001 level (two-tailed).

Additional Analyses

A separate one sample t-test revealed that participants’ standardized PHC scores

[t(46)=-5.086, p<.001, d=-1.05] and MHC scores [t(46)=-6.116, p<.001, d=-1.26] were

lower than standardized population PHC and MHC scores (M=50.00, SD=10.00). These

results are consistent with previous research showing lower health related quality of life in

people with SMI compared with the general population (Evans et al., 2007; Folsom et al.,

2009; Ritsner et al., 2002; Schechter et al., 2007).

Bivariate correlations revealed significant associations between the MHC of the

SF-36 and with years of education (r = .332, p<.05), positive and negative symptoms as

measured by the BPRS-E (r = -.387, p<.01), and depressive symptoms as measured by the

HAM-D (r = -.656, p<.001). Bivariate correlations also demonstrated a significant negative

relationship between the PHC of the SF-36 and the number of reported medical conditions

29

(r = -.464, p<.001). Age, gender, race, marital status, living situation and work status were

not significantly related to MHC or PHC scores in this sample.

30

CHAPTER 5

DISCUSSION

The purpose of this study was to investigate the predictive ability of the PHC of the

SF-36 on subjective quality of life in people with serious mental illness. Previous quality

of life models have shown mixed results when investigating the factors that influence QOL

in this population. Due to the high prevalence of medical comorbidity, and research within

the general population showing lower quality of life among people with physical health

limitations, this study examined health related quality of life due to physical health factors

as distinct from mental health factors. This study differs from previous research in that it

directly compared self-reported role limitations due to physical health to self-reported role

limitations due to mental health.

The first hypothesis for this study, that participant’s reports of role limitations due

to physical health would be higher than role limitations due to mental health factors, was

not supported. Although there were no differences in the MHC and PHC scores of the SF-

36, these results are still meaningful as they show that people with SMI are at least as

concerned with their physical health as they are their mental health. Compared with the

general population, health related quality of life in this sample was significantly lower, and

is consistent with previous research. These results demonstrate that people with SMI report

as many role limitations due to physical health as they do mental health. The recognition of

physical health care needs is consistent with national and state mental health initiatives

which utilize both mental health and physical health as part of a whole-body approach to

wellbeing.

31

In order to investigate the relative contribution of physical health in subjective

QOL, the second hypothesis proposed that physical health of people with SMI would be

more predictive of overall quality of life than would mental health. In the current model,

the PHC was able to explain a substantial amount of variance in quality of life scores

beyond what was already explained by mental health factors. Depressive symptoms, role

limitations due to mental health, and role limitations due to physical health significantly

increased the predictive ability of an overall QOL model, and independently, were

significant related to quality of life. Positive and negative symptoms, as measured by the

BPRS-E, did not significantly add to the explained amount of variance in the model.

Correlational analyses also failed to demonstrate a significant relationship between

psychiatric symptoms and quality of life, which is consistent with previous research

(Ritsner et al., 2006). Although role limitations that people experienced due to mental

illness did influence overall quality of life ratings, the role limitations people with SMI

experienced due to physical health was significantly more distressing. Overall, 78% of the

variance in quality of life scores was explained from this proposed model. Consistent with

hypothesis two, PHC provided the strongest unique predictive contribution to subjective

QOL even after controlling for other predictive factors such as depression and mental

health.

Depression was included as the first predictor in the model in order to capture its

unique contribution to overall quality of life. Independently, greater depressive symptoms

were predictive of lower quality of life, however this relationship did not remain

significant with the inclusion of positive and negative symptoms and health related quality

32

of life scores. Depression and quality of life were negatively associated, indicating that

people who reported greater depressive symptoms also reported a lower quality of life.

These results provide evidence that although depression and quality of life are strongly

related, additional factors such as physical health also have a strong influence on subjective

quality of life.

MHC also emerged as a significant predictor of overall quality of life even after

controlling for symptoms. The MHC component of the SF-36 is comprised of questions

related to overall mental health, energy and fatigue, social functioning, and role limitations

due to mental health problems. Because people with serious mental illness typically report

difficulties in these life domains, this finding was not unexpected, and highlights areas to

target for intervention and research. Construct validity for the model is supported with

MHC emerging as an independent predictor in the proposed model, as it would be

expected that people with serious mental illness would also report significant role

limitations due to mental health.

Most importantly, and the overall purpose of this study, was that PHC was able to

significantly predict overall quality of life scores after controlling for the effects of

depression, psychiatric symptoms, and mental health factors. The PHC component of the

SF-36 is comprised of questions related to general health, physical functioning, bodily

pain, and role limitations due to physical health problems. This is especially noteworthy

given that the mean scores of role limitations due to physical and mental health were not

significantly different, indicating a stronger effect of physical health, rather than mental

health, on quality of life. Given the high rates of medical co-morbidity, it may be more

33

meaningful to focus on health -related quality of life, as measured by the SF-36 in a SMI

population.

Interestingly, in a second regression model that did not control for the effects of

depression, positive and negative psychiatric symptoms independently were not a

significant predictor of quality of life, however MHC and PHC continued to explain up to

76% of overall quality of life scores. This model also continued to show physical health as

the strongest predictor of quality of life. Interpretation of this model suggests that although

depressive symptoms are a unique contributor to overall quality of life, physical health

remains a distinct area of concern affecting quality of life in people with SMI.

Limitations

One of the primary limitations of this study was the lack of statistical power to

include additional predictors in the model. Previous research has shown both community

and social functioning as being significantly related to quality of life in people with SMI,

however this limited sample size did not allow for testing of additional predictors (Test et

al., 2005; Tolman & Kurtz, 2010). Other published quality of life models have found a

significant effect of social factors on quality of life in people with SMI. For example,

Dufort, Dallaire, & Lavoie (1997) found that an effective social support network was able

to independently account for 16% of overall variance in a six factor global quality of life

model. It is therefore important to note that the model proposed in the current study is not

comprehensive, but represents the role of more global factors (overarching mental health

and physical health) that impact quality of life. Future research should include additional

34

known predictors of QOL into a more comprehensive model including physical, mental

and social factors.

A further limitation of this study is that generalization may be weak within the SMI

community. The participants in this sample were all participating in a formally structured

outpatient day program with convenient access to medical care, mental health care and

case management. As such, the results of this sample may not be replicated in individuals

in other contexts. However, it could be hypothesized, that in a less comprehensive

treatment environment, people without access to health care would most likely report even

greater difficulties due to physical and mental health, which would further strengthen the

model. Further research should help clarify the potential role of health care access on QOL.

Also, variance explained in the model by physical health may be artificially inflated

due to item overlap between the PHC component of the SF-36 and the Q-LES-Q that is not

present within the MHC. Specifically, the Q-LES-Q contains a subdomain of physical

health that includes four of the 18 total items. Therefore, internal validity may be

weakened by using this particular health survey in order to predict overall quality of life.

Last, accuracy of data collected by self-report is questionable, and much of the data

in this study was subjective, which may differ from objectively measured mental and

physical health. It could be argued, however, that subjective assessment of quality of life

may be the most meaningful constructs to capture in QOL research.

Conclusion

Overall, outcome research has revealed that improvements in cognition, reduction

of psychotic symptoms, and access to social services may be necessary, but not sufficient

35

methods of improving quality of life in people with serious mental illness (Test et al.,

2005; Tolman & Kurtz, 2010). Physical illness has become a cornerstone feature of serious

mental illness, and an overwhelming body of evidence shows that individuals with SMI

have increased mortality rates more than five times higher than the general population

(Kelly et al., 2007). In light of current findings, researchers and clinicians should focus on

a comprehensive view of health, addressing both the mental and physical health concerns

and limitations in people with serious mental illness. There is growing recognition that

recovery and QOL improvements are realistic goals for persons with schizophrenia and as

such, there is a need for research on relevant outcomes such as people’s subjective

experience of quality of life. Current quality of life research indicates increasing concern

and self-reported dissatisfaction with physical health (Dufort et al., 1997). As quality of

life becomes an important goal for outcome research, incorporating physical health into a

comprehensive model of overall wellness may have positive implications for recovery

among persons with SMI. Given the importance placed on subjective and recovery-based

treatment orientations, it is important for research to continue to explore the strengths and

limitations of quality of life measures in persons with SMI.

36

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42

VITA

Amy Lee Barnes was born on August 1st, 1972 in Memphis, TN. She was educated

in the public school system in Springfield, IL where she graduated from Lanphier High

School in 1990. Amy attended the University of Illinois at Springfield and was a member

of Psi Chi national honor society in psychology, including holding the office of Vice

President of Psi Chi. Amy presented at several academic conferences and received the

Independent Student Research Recognition Award in addition to the Undergraduate

Student Research Grant. Amy earned her Bachelor of Arts degree in 2007 and graduated

Magna Cum Laude with a major in Psychology.

Prior to graduation from UIS, Amy was accepted to the Clinical Health Psychology

program at the University of Missouri – Kansas City. She began the program in Fall 2007.

Since that time Amy has contributed to several poster presentations and one published

work in the Journal of Pharmaceutical Education. Amy has been awarded the Gerre Gene

Strauss research award and the Audrey Langworthy research award. Amy is currently a

member of the Association of Cognitive and Behavioral Therapies and the American

Psychological Association.